DeepPlantAllergy: deep learning for explainable prediction of allergenicity in plant proteins.

While the ROC-AUC variation remained nonsignificant when attention was removed ( P -value = .92), eliminating CNN and BiLSTM shifted the balance, giving advantage to ProtBert over ESM-1B embeddings, resulting in a borderline significance for NoLSTM (97.86% versus 97.28%, P = 0.049), and a pronounced significance for NoCNN (97.40% versus 96.63%, P -value = .007).

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